Triple
T22055869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spain–Portugal border |
E545007
|
entity |
| Predicate | hasSectionCharacteristic |
P146429
|
FINISHED |
| Object | rural borderlands |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: rural borderlands | Statement: [Spain–Portugal border, hasSectionCharacteristic, rural borderlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionCharacteristic Context triple: [Spain–Portugal border, hasSectionCharacteristic, rural borderlands]
-
A.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
B.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
C.
hasSect
Indicates that an entity includes, contains, or is associated with a particular sect or subgroup within a larger religious, ideological, or organizational context.
-
D.
hasSectionWith
Indicates that an entity contains or includes a specific section that satisfies certain conditions or characteristics.
-
E.
hasSectionRole
Indicates that an entity holds a specific role or function within a particular section or subdivision of a larger structure or context.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285790948190b21abfb09abbb5e5 |
completed | April 28, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:26 p.m.